In the art, a number of diseases are diagnosed using classical cytopathology methods involving examination of nuclear and cellular morphology and staining patterns. Typically, such diagnosis occurs by the examination of up to 10,000 cells in a sample and the finding of about 10 to about 50 cells that are abnormal. This finding is based on subjective interpretation of visual microscopic inspection of the cells in the sample.
An example of such classical cytology dates back to the middle of the last century, when Papanicolaou introduced a method to monitor the onset of cervical disease by a test, commonly known as the “Pap” test. For this test, cells are exfoliated using a spatula or brush, and deposited on a microscope slide for examination. In the original implementation of the test, the exfoliation brush was smeared onto a microscope slide, hence the name “Pap smear.” Subsequently, the cells were stained with hematoxylin/eosin (H&E) or a “Pap stain” (which consists of H&E and several other counterstains), and inspected visually by a cytologist or cyto-technician, using a low power microscope (see FIGS. 1A and 1B for Photostat images of an example Pap smear slide and a portion thereof under 10× microscopic magnification, respectively).
The microscopic view of such samples often shows clumping of cells and contamination by cellular debris and blood-based cells (erythrocytes and leukocytes/lymphocytes). Accordingly, the original “Pap-test” had very high rates of false-positive and false-negative diagnoses. Modern, liquid-based methods (such as cyto-centrifugation, the ThinPrep® or the Surepath® methods) have provided improved cellular samples by eliminating cell clumping and removing confounding cell types (see, e.g., example Photostat image of a 10× magnification microscopic view of a cytologic sample prepared by liquid-based methods, shown in FIG. 2).
However, although methods for the preparation of samples of exfoliated cells on microscope slides have improved substantially, the diagnostic step of the art still typically relies on visual inspection and comparison of the results with a data base in the cytologist's memory. Thus, the diagnosis is still inherently subjective and associated with low inter- and intra-observer reproducibility. To alleviate this aspect, other art automated visual light image analysis systems have been introduced to aid cytologists in the visual inspection of cells. However, since the distinction of atypia and low grades of dysplasia is extremely difficult, such art automatic, image-based methods have not substantially reduced the actual burden of responsibility from the cytologist.
Spectral methods have also been applied in the art to the diagnosis of tissue sections available from biopsy. The data acquisition for this approach, referred to as “Spectral Histopathology (SHP),” can be carried out using the same visual light based instrumentation used for spectral cytopathology (“SCP”).
FIGS. 3A and 3B show Photostats of the results of SHP for the detection of metastatic cancer in an excised axillary lymph node using methods of the art. FIG. 3A shows a micrograph of the H&E stained image of axillary lymph node tissue, with regions marked as follows: 1) capsule; 2) normal lymph node tissue; 3) medullary sinus; and 4) breast cancer metastasis. To obtain the Photostat image shown in FIG. 3B, collected infrared spectral data were analyzed by a diagnostic algorithm, trained on data from several patients, which subsequently is able to differentiate normal and cancerous regions in the lymph node. In FIG. 3B, the Photostat shows the same tissue as in FIG. 3A constructed by supervised artificial neural network trained to differentiate normal and cancerous tissue only. The network was trained with data from 12 patients.
In some methods of the art, a broadband infrared (IR) or other light output is transmitted to a sample (e.g., a tissue sample), using instrumentation, such as an interferometer, to create an interference pattern. Reflected and/or passed transmission is then detected, typically as another interference pattern. A Fast Fourier Transform (FFT) may then be performed on the ratioed pattern to obtain spectral information relating to the sample.
One limitation with this FFT based art process is that the amount of energy available per unit time in each band pass may be very low, due to use of a broad spectrum transmission, which may include, for example, both IR and visible light. As a result, the data available for processing are generally inherently limited with this approach. Further, in order to discriminate the received data from background noise, for example, with such low detected energy data available, high sensitivity instruments must be used, such as high sensitivity liquid nitrogen cooled detectors (which cooling thereby alleviates the effects of background IR interference). Among other drawbacks, such art systems may incur great costs, and require the use of refrigerants.
In one art device produced by Block Engineering (see, e.g., J. Coates, “Next-Generation IR Microscopy: The Devil Is in the Detail,” BioPhotonics (October 2010) pp. 24-27), which proposes to use a QCL without an interferometric imager, no device or system has been identified to suitably coordinate operation between the QCL and the imager.
There remains an unmet need in the art for devices, methods, and systems for transmitting and detecting IR and/or other similar transmissions for use, for example, for imaging tissue samples and other samples under ambient conditions for such purposes as the diagnosis of disease.